Artificial Intelligence in Epigenetic Studies: Shedding Light on Rare Diseases

Frontiers in Molecular Biosciences

Cátia José Neves¹  Marta Falcão²  Gonçalo Valadão³  Sandra Brasil³  Tatiana Rijoff³  Vanessa dos Reis Ferreira⁴  Paula A. Videira⁷ 

[1] Allies – PPAIN), Caparica, Portugal;;Allies – Professionals and Patient Associations International Network (CDG &;CDG &Departamento de Ciências e Tecnologias, Autónoma Techlab — Universidade Autónoma de Lisboa, Lisbon, Portugal;Instituto de Telecomunicações, Lisbon, Portugal;Portuguese Association for CDG, Lisbon, Portugal;UCIBIO, Departamento de Ciências da Vida, Faculdade de Ciências e Tecnologia, Universidade NOVA de Lisboa, Lisbon, Portugal;

关键词: epigenetics;    epigenomic;    artificial intelligence;    machine learning;    personalized medicine;    rare diseases (RD);   

DOI  :  10.3389/fmolb.2021.648012

来源: DOAJ

【 摘 要 】

More than 7,000 rare diseases (RDs) exist worldwide, affecting approximately 350 million people, out of which only 5% have treatment. The development of novel genome sequencing techniques has accelerated the discovery and diagnosis in RDs. However, most patients remain undiagnosed. Epigenetics has emerged as a promise for diagnosis and therapies in common disorders (e.g., cancer) with several epimarkers and epidrugs already approved and used in clinical practice. Hence, it may also become an opportunity to uncover new disease mechanisms and therapeutic targets in RDs. In this “big data” age, the amount of information generated, collected, and managed in (bio)medicine is increasing, leading to the need for its rapid and efficient collection, analysis, and characterization. Artificial intelligence (AI), particularly deep learning, is already being successfully applied to analyze genomic information in basic research, diagnosis, and drug discovery and is gaining momentum in the epigenetic field. The application of deep learning to epigenomic studies in RDs could significantly boost discovery and therapy development. This review aims to collect and summarize the application of AI tools in the epigenomic field of RDs. The lower number of studies found, specific for RDs, indicate that this is a field open to expansion, following the results obtained for other more common disorders.

【 授权许可】

Unknown